半导体学报2007，Vol.28Issue(9)：1375-1380,6.
基于最大电源噪声门级模型的遗传算法电源噪声估计
Combined Novel Gate Level Model and Critical Primary Input Sharing for Genetic Algorithm Based Maximum Power Supply Noise Estimation
摘要
Abstract
A gate level maximum power supply noise (PSN) model is defined that captures both IR drop and di/dt noise effects. Experimental results show that this model improves PSN estimation by 5.3% on average and reduces computation time by 10.7% compared with previous methods. Furthermore,a primary input critical factor model that captures the extent of primary inputs' PSN contribution is formulated. Based on these models,a novel niche genetic algorithm is proposed to estimate PSN more effectively. Compared with general genetic algorithms, this novel method can achieve up to 19.0% improvement on PSN estimation with a much higher convergence speed.关键词
电源噪声/门极模型/小生境遗传算法Key words
power supply noise/gate level model/niche genetic algorithm分类
信息技术与安全科学引用本文复制引用
田志新,刘勇攀,杨华中..基于最大电源噪声门级模型的遗传算法电源噪声估计[J].半导体学报,2007,28(9):1375-1380,6.基金项目
Project supported by the National Natural Science Foundation of China (No. 90207001) 国家自然科学基金资助项目(批准号:90207001) （No. 90207001）
